import * as tf from '@tensorflow/tfjs';
import { CropAndResizeAspectRatio, ImageTensor } from '../image-utils';
import { ImageModelSpec } from '../image-model';
/**
 * @example `loadGraphModel({ url: 'saved_model/mobilenet-v3-large-100' })`
 */
export declare function loadGraphModel(options: {
    url: string;
    classNames?: string[];
}): Promise<tf.GraphModel<string | tf.io.IOHandler> & {
    classNames?: string[];
}>;
/**
 * @example `loadGraphModel({ url: 'saved_model/emotion-classifier' })`
 */
export declare function loadLayersModel(options: {
    url: string;
    classNames?: string[];
}): Promise<tf.LayersModel & {
    classNames?: string[];
}>;
/**
 * @example ```
 * cachedLoadGraphModel({
 *   url: 'saved_model/mobilenet-v3-large-100',
 *   cacheUrl: 'indexeddb://mobilenet-v3-large-100',
 * })
 * ```
 */
export declare function cachedLoadGraphModel(options: {
    url: string;
    cacheUrl: string;
    checkForUpdates?: boolean;
    classNames?: string[];
}): Promise<tf.GraphModel<string | tf.io.IOHandler> & {
    classNames?: string[];
}>;
/**
 * @example ```
 * cachedLoadLayersModel({
 *   url: 'saved_model/emotion-classifier',
 *   cacheUrl: 'indexeddb://emotion-classifier',
 * })
 * ```
 */
export declare function cachedLoadLayersModel(options: {
    url: string;
    cacheUrl: string;
    checkForUpdates?: boolean;
    classNames?: string[];
}): Promise<tf.LayersModel & {
    classNames?: string[];
}>;
export type ImageModel = Awaited<ReturnType<typeof loadImageModel>>;
/**
 * @description cache image embedding keyed by filename.
 * The dirname is ignored.
 * The filename is expected to be content hash (w/wo extname)
 */
export type EmbeddingCache = {
    get(url: string): number[] | null | undefined;
    set(url: string, values: number[]): void;
};
export declare function loadImageModel<Cache extends EmbeddingCache>(options: {
    url: string;
    cacheUrl?: string;
    checkForUpdates?: boolean;
    aspectRatio?: CropAndResizeAspectRatio;
    cache?: Cache | boolean;
}): Promise<{
    spec: ImageModelSpec;
    model: tf.GraphModel<string | tf.io.IOHandler>;
    fileEmbeddingCache: Map<string, tf.Tensor<tf.Rank>> | null;
    checkCache: (url: string) => tf.Tensor | void;
    loadImageCropped: (url: string) => Promise<tf.Tensor4D & tf.Tensor<tf.Rank>>;
    imageUrlToEmbedding: (url: string) => Promise<tf.Tensor>;
    imageFileToEmbedding: (file: File) => Promise<tf.Tensor>;
    imageTensorToEmbedding: (imageTensor: ImageTensor) => tf.Tensor;
}>;